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The probable role of insulin resistance and SIRT1 proteins in the Alzheimer's disease
No full textObjective: Recent evidence suggests that insulin resistance may play an
important role in the pathogenesis of Alzheimer's disease (AD). In this
study, the probable role of insulin resistance in the pathogenesis of AD
was investigated in patients with Type 2 Diabetes Mellitus (T2DM).
Methods: Serum amyloid beta (A beta) (1-42), insulin like growth
factor-1 (IGF-1), sirtuin1 (SIRT1) and leptin protein levels were
measured in serum samples of control (n = 26), probable AD (n = 26), and
probable AD+T2DM patients (n = 12) using ELISA method. Mini mental state
examination (MMSE) was performed to the patient and control groups.
Result: Serum IGF-1 significantly increased in the probable AD+T2DM
group as compared to the control and probable AD groups (p < 0.05). The
levels of serum leptin significantly decreased in the probable AD and
AD+T2DM groups as compared to the control (p < 0.05). There were no
statistically significant differences in serum A beta (1-42) and SIRT1
levels among groups (p > 0.05).
Conclusion: The significant decrease in serum leptin levels in AD
patients may indicate that it may be a therapeutic marker in AD. The
level of serum A beta peptide and SIRT1 proteins can vary depending on
the stage of the disease. Therefore, this study should be supported by
more comprehensive studies in terms of the number of patients in
advanced stage (Tab. 1, Fig. 4, Ref. 29)
Parameters of complete blood count might predict the prognosis of patients with advanced gastric cancer
No full textEvaluation of a two-image technique consisting of an axial and a coronal image generated by using the rib-flattening application: Effect on reading time and diagnostic validity
No full textAISI T15 Çeliğinin İşlenmesinde PVD TiAlN + Al203 ve CVD TiCN+TiN Kaplama Performansının Araştırılması
No full textSedative and anxiolytic activities of Opuntia ficus indica (L.) mill.: An experimental assessment in mice
No full textIbrutinib plus CIT for R/R mature B-NHL in children (SPARKLE trial): initial safety, pharmacokinetics, and efficacy
No full textDus Weıbull And Dus Inverse Weıbull Dıstrıbutıons: Parameter Estımatıon And Hypothesıs Tests
No full textİstatistik, mühendislik, tıp, finans gibi birçok uygulamalı bilimde gerçek veri setlerinin
analiz edilmesi ve modellenmesi oldukça önemlidir. Doğadaki rasgelelikten dolayı,
sistemlerin bozulma davranışları doğal mekanizmalarına bağlı olarak çeşitlilik gösterebilir.
Sistemlerin bahsedilen bozulma davranışları istatistiksel modeller yardımıyla açıklanabilir.
Bu amaçla literatürde yaşam verilerini modellemek için önerilen birçok yaşam süresi
dağılımı vardır. Bununla birlikte mevcut standart olasılık dağılımlarının kısıtlamaları veya
modelleme yetersizlikleri araştırmacıları mevcut dağılımları genelleştirme ya da yeni
dağılım aileleri önermeye itmiştir. Yeni dağılım aileleri üreten tekniklerden biri de DUS
dönüşüm tekniğidir. Bu teknik, hesaplama ve yorumlama açısından daha kolay ve anlaşılır
ayrıca yeni parametre içermeyen bir dağılım üretir. Bu çalışmada, Weibull ve inverse
Weibull dağılımları temel dağılım olarak alınıp, DUS-Weibull ve DUS-inverse-Weibull
dağılımları önerilmiştir. Önerilen dağılımların momentleri, basıklık ve çarpıklık katsayıları,
moment çıkaran fonksiyonları ve quantil fonksiyonları gibi istatistiksel özellikleri ortaya
konmuştur. Ayrıca farklı tahmin metotları için önerilen dağılımların bilinmeyen
parametrelerinin tahmin edicilerinin etkinliklerini karşılaştırmak için Monte Carlo
simülasyon çalışması yapılmıştır. Önerilen dağılımların lineer modellere uygulanmasını
göstermek amacıyla, DW ve DIW dağılımları lineer regresyon modeline uygulanmıştır.
Lineer regresyon modelinde bilinmeyen parametreleri tahmin etmek için genellikle hataların
dağılımının ortalaması 0 varyansı 2 olan normal dağılıma sahip oldukları varsayılır. Ancak
çoğu uygulamada genellikle hatalar normal dağılıma sahip olmazlar. Bu çalışmada, lineer
regresyon modeli için, hataların dağılımı DW ve DIW olarak alınmıştır. Daha sonra,
bilinmeyen regresyon parametreleri tahmin edilmiş ve bu parametrelere dayalı olarak
hipotez testi için yeni test istatistikleri önerilmiştir. Önerilen regresyon tahmin edicilerinin
performansları ve bunlara dayalı testler Monte Carlo simülasyon çalışması ile
karşılaştırılmıştır. Çalışmanın sonunda, önerilen metedolojilerin uygulanabilirliğini
göstermek için bir uygulama çalışması verilmiştir.In many applied sciences such as statistics, engineering, medicine, finance, the analysis and
modeling of real data sets is very important. Due to the randomness in nature, the
deterioration behavior of the systems may vary depending on their natural mechanisms. This
distortion behavior of the systems can be explained with the help of statistical models. For
this purpose, there are many life time distributions proposed in the literature to model life
data. However, limitations or modeling insufficiencies of existing standard probability
distributions have led researchers to generalize existing distributions or propose new
distribution families. One of the techniques that produce new distribution families is the
DUS transformation technique. This technique produces a parsimonious distribution in
terms of computation and interpretation as it never contain any new parameter. In this study,
Weibull and inverse Weibull distributions are taken as the basic distributions and DUSWeibull
(DW) and DUS-inverse-Weibull (DIW) distributions are proposed. Moments,
kurtosis and skewness coefficients, moment generating functions and quantile functions of
the proposed distributions are presented. In addition, Monte Carlo simulation study is
conducted to compare the efficiencies of the estimators of the unknown parameters of the
proposed distributions for different estimation methods. In order to demonstrate the
application of the proposed distributions to linear models, DW and DIW distributions are
applied to the simple linear regression model. To estimate unknown parameters in a linear
regression model, it is generally assumed that the distributions of errors have a normal
distribution with mean 0 and variance 2 . In practice, however, errors do not have a normal
distribution in most of the practical cases. In this study, for the linear regression model, the
distribution of the errors is taken to be DW and DIW. Then, we estimate the unknown
regression parameters and propose new test statistics based on them to test the hypotheses.
Performances of the proposed regression estimators and the tests based on them are
compared via Monte Carlo simulation study. An application is given at the end of the study
to show the implementation of the proposed methodologie
Plazma arkı ile kesim işlemlerinde kesme parametrelerinin malzemenin kesim yüzeyi kalitesine ve ısı tesiri altındaki bölge (ITAB) genişliğine etkisinin deneysel olarak araştırılması
No full textMicrowave-Assisted Synthesis of Stretchable and Transparent Poly(Ethyleneglycol-Sebacate) Elastomers with Autonomous Self-Healing and Capacitive Properties
No full textIntroducing functional synthetic biomaterials to the literature became
quite essential in biomedical technologies. For the growth of novel
biomedical engineering approaches, progressive functional properties as
well as the robustness of the manufacturing processes are essential. By
using acid-induced epoxide ring-opening polymerizations through
catalysts, a wide variety of biodegradable and functionalized
biomaterials can be synthesized. Sebacic acid (SA) and poly(ethylene
glycol) diglycidyl ether (PEGDGE) are amongst the FDA-approved
biocompatible materials. In this study, we focused on the rapid
synthesis of caffeine-catalyzed self-healable elastomer via a facile
microwave-assisted synthesis route. The elastomer prepared can be used
in various applications, including tactile sensors, wearable
electronics, and soft robotics. SA and PEGDGE were catalyzed in the
presence of caffeine under microwave irradiation followed by
crosslinkingin vacuo, yielding an elastomeric material. The chemical
characterizations of the obtained elastomer were carried out. The
resulting material is transparent, highly stretchable, and has
capacitive and self-healing properties even at room temperature. The
material developed can be easily applied for the aforementioned
applications